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How to Monitor Transaction Governance for Anti-Money Laundering

Posted by Protiviti KnowledgeLeader on Tue, Mar 17, 2020 @ 11:00 AM

""Expectations for transaction monitoring (TM) governance are quickly evolving due to the complexity of detection systems, the demand for additional operational oversight, increased regulatory scrutiny and the need for an adequate control framework to guarantee proper risk management.

As a result, compliance officers/anti-money laundering (AML) officers/money laundering reporting officers (collectively, MLROs), along with other affected financial institution personnel, are finding it increasingly difficult to manage their existing responsibilities amid the heightened scrutiny and expectations regulators have regarding transaction monitoring systems and the end-to-end (E2E) processes tied to them (e.g., vendor selection, tuning rationale, model validation requirements, backlogs, etc.).

CHALLENGES AND OPPORTUNITIES

Organizations face the following challenges concerning designing a strong TM governance control framework:

  • Manage regulatory expectations. In addition to overseeing the day-to-day operations of clearing alerts and performing investigations, regulators expect institutions nowadays to ensure the integrity of the data, tune/enhance monitoring scenarios and validate the effectiveness of the systems on an ongoing basis.
  • Tune methodology and know-how. Some institutions may lack the expertise in this area to develop scenarios effectively, fine-tune them and ensure that they are designed to cover known money laundering red flags. In some cases, this may be since institutions relied on vendors/consultants to implement the TM systems and never retained the knowledge within the organization. When presented with questions by auditors/regulators, MLROs may be unable to respond with the level of knowledge or detail that is expected
  • Establish a working relationship with multiple parties. TM programs depend on critical inputs provided by the business team about how products are intended to be used by customers, as well as on inputs from the compliance team about money laundering red flags/typologies associated with each product. A lack of collaboration between compliance, business and technology teams inhibits an informed scenario-tuning process that is based on data and the expert judgment of end users and risks.
  • Achieve global consistency. For larger institutions with a global footprint, ensuring that each region has hired the right people, implemented adequate detection scenarios and instituted strong controls to manage the end-to-end TM process has become a significant challenge. This is due to geographical distance from the head office, differences in regulatory requirements, and misinterpretation of regulations and/or internal policies and procedures.
  • Manage the alert investigation team. The teams involved in the alert review process may be growing quickly, making it difficult to ensure that everyone on the team has the required skill set and expertise to review the output of the TM systems (alerts). It also may be difficult within a rapidly growing unit to manage the quality of the rationale used by investigators to close an alert or escalate it and document suspicion. Some larger institutions may offshore the alert review process, which adds to the difficulties in providing oversight, guidance and timely feedback.
  • Measure success/effectiveness. Traditional numbers-based metrics do not show the full picture when it comes to TM efforts. Many institutions struggle with determining how best to measure success since efficiency benchmarks alone do not guarantee effectiveness.

Learn more about AML by exploring these related tools on KnowledgeLeader:

An Urgent Call for KYC Optimization
Transforming AML Compliance With Technology
Can Machine Learning Improve Consumer Lending? We Think So

Topics: Enterprise Risk Management, Laws & Regulations, Fraud, Foreign Corrupt Practices Act, Compliance, Financial Services Industry

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